D Deep sequencing of CNR1 gene network in substance dependence: Abstract This Mentored Research Career Development Award (K01) is to train Dr. Lingjun Zuo, a junior faculty member of Department of Psychiatry at Yale University, to become an independent investigator in the research field on genetics of substance dependence (SD). The trainings include three main areas: (1) advanced human molecular genetics, in particularly in Solexa sequencing and cannabinoid receptor 1 (CNR1) gene network; (2) neuroscience, in particularly in SD, brain neural networks and functional relationship between cannabinoid receptor and protein product of other SD candidate genes; and (3) bioinformatic and statistical analytical methods for high-throughput sequence data, gene network data as well as gene x environment interaction analysis. To acquire these trainings, Dr. Zuo's time will be allocated (1) to courses and seminars, (2) to meetings with the mentor and co-mentors, (3) to interactions with other experts, and mainly (4) to the proposed research project per se. The research plan will focus on deep sequencing of CNR1 gene network that consists of CNR1 and five other biologically related genes. Dr. Zuo proposes to identify the potential functional variants underlying SD in this gene network by (1) sequencing the targeted gene regions in a relatively big size of sample using next generation sequencing approach, and by (2) using multiple-gene model to investigate the joint effects of multiple functional variants, which might exert too weak individual effects to be detectable using single-gene model. This proposed study would be promising to elucidate the genetic variants in the CNR1 gene network underlying SD, which would make a major progress in the etiology of SD, and may also be helpful to develop novel and effective treatment and prevention strategies for SD. PUBLIC HEALTH RELEVANCE: Relevance to public health This proposed project will carefully study the effects of cannabinoid receptor 1 gene (CNR1) network on risk for substance dependence (SD) using the next generation deep sequencing technology, which will help us better understand the mechanism for the development of SD. The expected findings would significantly contribute to the improvement of public health.